{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "44XcS8RpA4JG"
   },
   "source": [
    "# Meter Swapping Detection\n",
    "\n",
    "Electricity theft is a huge problem for the Energy industry and a well-known and documented technique to steal energy is meter-swapping. Imagine two electricity consumers $A$ and $B$. Consumer $A$ is energy-efficient and do not consume a lot of electric energy, while household $B$ is a heavy consumer of electricity: he could be playing videogames too much, run the dishwasher 6 times a days or keep air conditioning on all the time. Now suppose that $B$ is a criminal mastermind and decides to switch his/her meter with that of $A$, this way he/she will effectively pay for $A$ small consumption, while $A$ will start receiving astronomical utility bills. \n",
    "\n",
    "A new paper by Zhu, Y. et al. (2020) [1] suggests that the Matrix Profile can be used to easily detect meter-swapping. In this tutorial we are going to use a dataset household electrical power demand collected from\n",
    "twenty houses in the UK, which you can download from [here](https://pureportal.strath.ac.uk/en/datasets/refit-electrical-load-measurements-cleaned) [2]. The dataset records electricity consumption every 6-8 seconds between 2013 and 2015."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "CMl0PsZyEvnx"
   },
   "source": [
    "## Load Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 119
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 3171,
     "status": "ok",
     "timestamp": 1600177462576,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "KC2wxTgcu2nx",
    "outputId": "1a92dd1f-7567-459e-fb5b-a55e56b60f89"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: stumpy in /usr/local/lib/python3.6/dist-packages (1.5.0)\n",
      "Requirement already satisfied: numba>=0.42.0 in /usr/local/lib/python3.6/dist-packages (from stumpy) (0.48.0)\n",
      "Requirement already satisfied: scipy>=1.2.1 in /usr/local/lib/python3.6/dist-packages (from stumpy) (1.4.1)\n",
      "Requirement already satisfied: numpy>=1.13 in /usr/local/lib/python3.6/dist-packages (from stumpy) (1.18.5)\n",
      "Requirement already satisfied: llvmlite<0.32.0,>=0.31.0dev0 in /usr/local/lib/python3.6/dist-packages (from numba>=0.42.0->stumpy) (0.31.0)\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from numba>=0.42.0->stumpy) (50.3.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install stumpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 3156,
     "status": "ok",
     "timestamp": 1600177462580,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
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    "id": "AroWGOriuLY9"
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import stumpy\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from zipfile import ZipFile\n",
    "from io import BytesIO\n",
    "import os\n",
    "import requests\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "\n",
    "plt.style.use('https://raw.githubusercontent.com/stumpy-dev/stumpy/main/docs/stumpy.mplstyle')\n",
    "\n",
    "np.random.seed(1337)  # Random seed for reproducibility"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DbvD23vkEz9I"
   },
   "source": [
    "## Load and clean data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Qv8wwbZfFelY"
   },
   "source": [
    "For each house, the dataset measures aggregate electricity consumption and single appliances' consumption. Because in our case we won't need to look at appliances, we will only load the `Aggregate` column. Also, loading data of all the 20 houses recorded in the study would be too heavy in terms of computations and it is not necessary to reproduce  the experiment of Zhu, Y. et al. (2020) [1]. Thus, we will only load data for House 1, 2, 3, 4 and 11."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 24071,
     "status": "ok",
     "timestamp": 1600177483517,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "08E36NwfuTM6"
   },
   "outputs": [],
   "source": [
    "#load data from Drive \n",
    "path = os.path.join(\"/content/drive/My Drive/\", \"consumption\") \n",
    "filenames = [f\"CLEAN_House{i}.csv\" for i in [1,2,3,4,11]]\n",
    "\n",
    "#load data into DataFrames and put them into a dictionary\n",
    "consumptions = {}\n",
    "for house in filenames:\n",
    "    consumptions[house] = pd.read_csv(os.path.join(path, house), usecols=[0, 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 24062,
     "status": "ok",
     "timestamp": 1600177483521,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "U5Nhodi5u7uh",
    "outputId": "3f9e1481-b704-47d8-c3ba-cbf8cd485436"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['House1', 'House2', 'House3', 'House4', 'House11']"
      ]
     },
     "execution_count": 207,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rename dictionary keys for easy access\n",
    "for key in list(consumptions.keys()):\n",
    "    consumptions[key[6:-4]] = consumptions.pop(key)\n",
    "list(consumptions.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 32103,
     "status": "ok",
     "timestamp": 1600177491578,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "s6SbEwrfi6RZ"
   },
   "outputs": [],
   "source": [
    "#convert column 'Time' to datetime format and sort dfs by date\n",
    "for i in [1,2,3,4,11]:\n",
    "    consumptions[f\"House{i}\"][\"Time\"] = pd.to_datetime(\n",
    "        consumptions[f\"House{i}\"][\"Time\"], infer_datetime_format=True\n",
    "    )\n",
    "    consumptions[f\"House{i}\"] = consumptions[f\"House{i}\"].sort_values(by=[\"Time\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "qPZcU2o0Fbo-"
   },
   "source": [
    "Now we can look at our dataframe. As we can see, we only have two columns: `Time` and `Aggregate`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 204
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 32093,
     "status": "ok",
     "timestamp": 1600177491581,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "sktEUbXRjDUW",
    "outputId": "173a037b-5756-4028-d865-96fa882378ec"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Aggregate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-10-09 13:06:17</td>\n",
       "      <td>523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-10-09 13:06:31</td>\n",
       "      <td>526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-10-09 13:06:46</td>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-10-09 13:07:01</td>\n",
       "      <td>532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-10-09 13:07:15</td>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Time  Aggregate\n",
       "0 2013-10-09 13:06:17        523\n",
       "1 2013-10-09 13:06:31        526\n",
       "2 2013-10-09 13:06:46        540\n",
       "3 2013-10-09 13:07:01        532\n",
       "4 2013-10-09 13:07:15        540"
      ]
     },
     "execution_count": 209,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "consumptions['House1'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Igiz0flRGaHj"
   },
   "source": [
    "FIrst of all, for our example we are going to take a subset of the data that goes from the 1st of May till the 23rd of December. We can easily filter all the 5 Houses DataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 32469,
     "status": "ok",
     "timestamp": 1600177491971,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "fc0rMHvRi67Q"
   },
   "outputs": [],
   "source": [
    "startdate = \"2014-01-01\"\n",
    "enddate = \"2014-12-31\"\n",
    "\n",
    "for i in [1,2,3,4,11]:\n",
    "  mask = (consumptions[f'House{i}'].Time >= startdate) & (consumptions[f'House{i}'].Time <= enddate)\n",
    "  consumptions[f'House{i}'] = consumptions[f\"House{i}\"][mask]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VNbl48ZbfD-r"
   },
   "source": [
    "Let's finally plot our consumption data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 417
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 36953,
     "status": "ok",
     "timestamp": 1600177496469,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
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     },
     "user_tz": -120
    },
    "id": "RKQeEo2Ddrno",
    "outputId": "03c9b1fc-de1a-43b8-b49e-f1ee06504165"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(5, sharex=True, gridspec_kw={\"hspace\": 0})\n",
    "plt.suptitle(\"Houses Consumptions (1, 2, 3, 4 and 11)\", fontsize=\"30\")\n",
    "\n",
    "ax = 0\n",
    "colors = ['green', 'red', 'blue', 'black', 'purple']\n",
    "\n",
    "for i, c in zip([1,2,3,4,11], colors):\n",
    "  axs[ax].plot(consumptions[f\"House{i}\"][\"Time\"], consumptions[f\"House{i}\"][\"Aggregate\"], color = c)\n",
    "  ax += 1 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 102
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 36937,
     "status": "ok",
     "timestamp": 1600177496472,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "c28RtkUnnk4n",
    "outputId": "7f6720b6-e90c-4328-e06a-2f6fc11487bc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3835951\n",
      "3575231\n",
      "4028495\n",
      "3838129\n",
      "2488428\n"
     ]
    }
   ],
   "source": [
    "#length of our dataframes\n",
    "for i in [1,2,3,4,11]: print(len(consumptions[f\"House{i}\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "57Y_ruqNcIbK"
   },
   "source": [
    "The electricity consumption data in our dataset is recorded every 6 to 8 seconds. Thus, each time series contains around 2.5 million data points. Although this provides high accuracy, it would take too much time to compute the matrix profiles of these time series. A simple solution is to use pandas `resample()`, a Convenience method for frequency conversion and resampling of time series. Thanks to this function we can resample our data to 5 minutes periods, dramatically reducing the size of our dataframes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 119
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 36921,
     "status": "ok",
     "timestamp": 1600177496479,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "-LDPvf1mtwHG",
    "outputId": "2716fdb7-9a1e-492b-de19-d583a1992d3d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New length of DataFrames\n",
      "8736\n",
      "7688\n",
      "8736\n",
      "8736\n",
      "5053\n"
     ]
    }
   ],
   "source": [
    "#resample data by grouping in 5 minute periods and take the mean.\n",
    "for i in [1,2,3,4,11]:\n",
    "  consumptions[f\"House{i}\"].set_index('Time',inplace=True)\n",
    "  consumptions[f\"House{i}\"] = consumptions[f\"House{i}\"].resample('H').mean()\n",
    "  consumptions[f\"House{i}\"].reset_index(level=0, inplace=True)\n",
    "\n",
    "print('New length of DataFrames')\n",
    "for i in [1,2,3,4,11]: print(len(consumptions[f\"House{i}\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mMj5YM7pix2t"
   },
   "source": [
    "## Meter-swapping detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "NIGAHNu1jakV"
   },
   "source": [
    "In order to simulate a meter-swapping event, we can randomly select two time series and swap their traces starting at October 1st. We are also going to compute Heads and Tails (consumption before and after October 1st) for all the other time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 36908,
     "status": "ok",
     "timestamp": 1600177496482,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "l_Ik8Qtki-4g"
   },
   "outputs": [],
   "source": [
    "#function to compute all heads and tails\n",
    "def heads_tails(cutoff):\n",
    "  heads, tails = {}, {}\n",
    "  for i in [1,2,3,4,11]:\n",
    "    heads[f'H_{i}'] = consumptions[f'House{i}'][consumptions[f'House{i}'].Time < cutoff]\n",
    "    tails[f'T_{i}'] = consumptions[f'House{i}'][consumptions[f'House{i}'].Time >= cutoff]\n",
    "  return heads, tails\n",
    "\n",
    "heads, tails = heads_tails(cutoff = \"2014-10-01\")\n",
    "\n",
    "#swap Heads and Tails of 1 and 11\n",
    "swap1, swap2 = 1, 11\n",
    "consumptions[f'House{swap1}'] = heads[f'H_{swap1}'].append(tails[f'T_{swap2}'])\n",
    "consumptions[f'House{swap2}'] = heads[f'H_{swap2}'].append(tails[f'T_{swap1}'])\n",
    "heads, tails = heads_tails(cutoff = \"2014-10-01\") #compute heads and tails again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 417
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 39080,
     "status": "ok",
     "timestamp": 1600177498670,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "HAPrHLu-jHIA",
    "outputId": "4719b2eb-8205-4907-c502-9548fb1c5530"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot after swap\n",
    "fig, axs = plt.subplots(5, sharex=True, gridspec_kw={\"hspace\": 0})\n",
    "plt.suptitle(\"Houses Consumptions\", fontsize=\"30\")\n",
    "\n",
    "ax = 0\n",
    "colors = ['green', 'red', 'blue', 'black', 'purple']\n",
    "for i, c  in zip([1,2,3,4,11], colors):\n",
    "    axs[ax].plot(consumptions[f\"House{i}\"][\"Time\"], consumptions[f\"House{i}\"][\"Aggregate\"], color = c)\n",
    "    axs[ax].axvline(x=datetime.date(2014, 10, 1), linestyle=\"dashed\", color = 'black')\n",
    "    ax += 1 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pG1ExnCsuY1K"
   },
   "source": [
    "It is pretty clear from the above plot that it is pretty difficult to detect meter-swapping thefts by naked eye. In order to detect the swapped Heads and Tails we can implement a simple algorithm that leverages the power of the Matrix Profile. \n",
    "\n",
    "We join all possible combinations of Heads and Tails, and record the pair $H_{i}$, $H_{j}$ that minimizes the following score:\n",
    "\n",
    "$\\text { Swap-Score }(i, j)=\\min \\left(\\operatorname{Head}_{\\mathrm{H} i} \\bowtie_\\theta 1 \\text { nn Tail }_{H j}\\right) /\\left(\\min \\left(\\operatorname{Head}_{\\mathrm{H} i} \\bowtie \\theta 1 \\text { nn Tail }_{H i}\\right)+\\text { epsilon }\\right)$\n",
    "\n",
    "\n",
    " $\\left(\\operatorname{Head}_{\\mathrm{H} i} \\bowtie \\theta 1 \\text { nn Tail }_{H j}\\right)$ is a vector of Euclidean distances between subsequences of $\\operatorname{Head}_{\\mathrm{H} i}$ and its nearest neighbor in $\\operatorname{Tail}_{\\mathrm{H} j}$. \n",
    "\n",
    "$\\left(\\operatorname{Head}_{\\mathrm{H} i} \\bowtie \\theta 1 \\text { nn Tail }_{H i}\\right)$ is a vector of Euclidean distances between subsequences of $\\operatorname{Head}_{\\mathrm{H} i}$ and its nearest neighbor in $\\operatorname{Tail}_{\\mathrm{H} i}$\n",
    "\n",
    "The equation looks a bit scary but the implementation in code will make things clearer.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 41855,
     "status": "ok",
     "timestamp": 1600177501460,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "JG0JclTSjNdT"
   },
   "outputs": [],
   "source": [
    "from numba import cuda\n",
    "m = 24 * 4#\n",
    "\n",
    "min_score = {}\n",
    "for i in [1,2,3,4,11]:\n",
    "  H_i, T_i = heads[f'H_{i}'].iloc[:, 1].astype(float), tails[f'T_{i}'].iloc[:, 1].astype(float)\n",
    "  mp = stumpy.stump(T_i, m, H_i, ignore_trivial=False)\n",
    "  mp_min = np.nanmin(mp[:, 0]) + 0.001\n",
    "  mp[mp == np.inf] = np.nan\n",
    "\n",
    "  for j in [1,2,3,4,11]:\n",
    "    T_j = tails[f'T_{j}'].iloc[:, 1].astype(float)\n",
    "    mp_j = stumpy.stump(T_j, m, H_i, ignore_trivial=False)\n",
    "    mp_j_min = np.nanmin(mp_j[:, 0])\n",
    "    mp_j[mp_j == np.inf] = np.nan\n",
    "    score = mp_j_min / mp_min\n",
    "\n",
    "    #code to record best score\n",
    "    if not min_score: min_score = dict(zip(['i', 'j', 'score', 'mp_j'], [i, j, score, mp_j])) #check if dict is empty\n",
    "    elif score < min_score['score']: min_score = dict(zip(['i', 'j', 'score', 'mp_j'], [i, j, score, mp_j]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 41842,
     "status": "ok",
     "timestamp": 1600177501463,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "aB2ceIHMl9oD",
    "outputId": "7d5d67a5-f283-47b9-ad87-aee746de938e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the sequences that minimize the score are:\n",
      "Head: H_11\n",
      "Tail: T_1\n"
     ]
    }
   ],
   "source": [
    "print('the sequences that minimize the score are:')\n",
    "min_i, min_j, mp_j = min_score['i'], min_score['j'], min_score['mp_j']\n",
    "print(f'Head: H_{min_i}')\n",
    "print(f'Tail: T_{min_j}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 136
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 41829,
     "status": "ok",
     "timestamp": 1600177501467,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "hHKa12mn7GHn",
    "outputId": "c3f39e19-0dbb-47b0-c774-ceb058d91ae5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'i': 11, 'j': 1, 'mp_j': array([[6.645445015139523, 156, -1, -1],\n",
       "        [6.646133462166893, 157, -1, -1],\n",
       "        [6.518721078147912, 158, -1, -1],\n",
       "        ...,\n",
       "        [5.347154576581185, 359, -1, -1],\n",
       "        [5.37326848973464, 360, -1, -1],\n",
       "        [5.284983426279912, 361, -1, -1]], dtype=object), 'score': 0.5078178753746648}"
      ]
     },
     "execution_count": 218,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VWeiuRmlGpMt"
   },
   "source": [
    "Our algorithm quickly discovered irregularities in the time series, thus we can quickly identify energy theft! Note that we have fixed cutoff time here, but if we want to, meter-swaps at other dates can be discovered by just increasing the search space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "i67nvdGhGe2B"
   },
   "source": [
    "## Plot the discovered motifs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 41817,
     "status": "ok",
     "timestamp": 1600177501471,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "aj2JsFMN3Tex"
   },
   "outputs": [],
   "source": [
    "idx = np.nanargmin(mp_j[:, 0])  # This is the index location for the smallest matrix profile distance\n",
    "match_idx = mp_j[idx, 1]  # This is the index location for the nearest neighbor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 434
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 41809,
     "status": "ok",
     "timestamp": 1600177501475,
     "user": {
      "displayName": "Jacopo Attolini",
      "photoUrl": "",
      "userId": "16577620843026715212"
     },
     "user_tz": -120
    },
    "id": "qChgkLfWSPHT",
    "outputId": "821726a4-b848-41ef-c7ae-ce735e4005c8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7efd45acddd8>]"
      ]
     },
     "execution_count": 220,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, sharex=False, gridspec_kw={\"hspace\": 0})\n",
    "plt.suptitle(\"Houses Consumptions\", fontsize=\"30\")\n",
    "\n",
    "axs[0].plot(heads[f'H_{min_i}'].iloc[idx:idx+m, 1], color = 'green')\n",
    "axs[1].plot(tails[f'T_{min_j}'].iloc[match_idx:match_idx+m, 1], color = 'red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "2amG6jCcD-Lq"
   },
   "source": [
    "## References\n",
    "\n",
    "[1] Zhu, Y. et al. (2020) “The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code,” Data Mining and Knowledge Discovery. Springer Science and Business Media LLC, 34(4), pp. 949–979. doi: 10.1007/s10618-019-00668-6.\n",
    "\n",
    "[2] Murray, D., Stankovic, L. and Stankovic, V., 2017. An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study. Scientific data, 4(1), pp.1-12.\n",
    "\n",
    "\n",
    "[STUMPY Documentation](https://stumpy.readthedocs.io/en/latest/)\n",
    "\n",
    "[STUMPY Matrix Profile Github Code Repository](https://github.com/stumpy-dev/stumpy)"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "authorship_tag": "ABX9TyOq4EASia3kfF3H82nC6uJE",
   "collapsed_sections": [],
   "mount_file_id": "1uJvR50Pv-6hs6bUQFyIgtE9GfMQmViW8",
   "name": "meter_swapping.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
